Relative commutants of strongly self-absorbing C*-algebras

The relative commutant $A'\cap A^{\mathcal{U}}$ of a strongly self-absorbing algebra $A$ is indistinguishable from its ultrapower $A^{\mathcal{U}}$. This applies both to the case when $A$ is the hyperfinite II$_1$ factor and to the case when it is a strongly self-absorbing C*-algebra. In the latter case we prove analogous results for $\ell_\infty(A)/c_0(A)$ and reduced powers corresponding to other filters on $\bf N$. Examples of algebras with approximately inner flip and approximately inner half-flip are provided, showing the optimality of our results. We also prove that strongly self-absorbing algebras are smoothly classifiable, unlike the algebras with approximately inner half-flip.Comment: Some minor correction

Isolates of Candida albicans that differ in virulence for mice elicit strain-specific antibody-mediated protective responses

Three distinct isolates of Candida albicans were used to establish systemic and oral infections in inbred mice that are genetically resistant or susceptible to tissue damage. Patterns of infection differed significantly between both yeasts and mouse strains. Systemic infection conferred significant protection against re-challenge with the homologous, but not the heterologous yeast; however, the protective effect was more evident in the tissue-susceptible CBA/CaH mice than in the resistant BALB/c strain. In contrast, oral infection induced protection against both homologous and heterologous oral challenge, although this was significant only in the CBA/CaH mice. CBA/CaH mice produced antibodies of both IgG1 and IgG2a subclasses, whereas BALB/c mice produced predominantly IgG1. Western blotting demonstrated considerable differences between epitopes recognised by serum antibodies from mice of both strains after immunisation with each of the three yeasts. Thus, different strains of yeast show considerable specificity in antibody responses elicited by either systemic or oral infection. (c) 2005 Elsevier SAS. All rights reserved

A convergence on Boolean algebras generalizing the convergence on the Aleksandrov cube

We compare the forcing related properties of a complete Boolean algebra B with the properties of the convergences $\lambda_s$ (the algebraic convergence) and $\lambda_{ls}$ on B generalizing the convergence on the Cantor and Aleksandrov cube respectively. In particular we show that $\lambda_{ls}$ is a topological convergence iff forcing by B does not produce new reals and that $\lambda_{ls}$ is weakly topological if B satisfies condition $(\hbar)$ (implied by the ${\mathfrak t}$-cc). On the other hand, if $\lambda_{ls}$ is a weakly topological convergence, then B is a $2^{\mathfrak h}$-cc algebra or in some generic extension the distributivity number of the ground model is greater than or equal to the tower number of the extension. So, the statement "The convergence $\lambda_{ls}$ on the collapsing algebra B=\ro ((\omega_2)^{<\omega}) is weakly topological" is independent of ZFC

A Non-invasive Technique to Detect Authentic/Counterfeit SRAM Chips

Many commercially available memory chips are fabricated worldwide in untrusted facilities. Therefore, a counterfeit memory chip can easily enter into the supply chain in different formats. Deploying these counterfeit memory chips into an electronic system can severely affect security and reliability domains because of their sub-standard quality, poor performance, and shorter lifespan. Therefore, a proper solution is required to identify counterfeit memory chips before deploying them in mission-, safety-, and security-critical systems. However, a single solution to prevent counterfeiting is challenging due to the diversity of counterfeit types, sources, and refinement techniques. Besides, the chips can pass initial testing and still fail while being used in the system. Furthermore, existing solutions focus on detecting a single counterfeit type (e.g., detecting recycled memory chips). This work proposes a framework that detects major counterfeit static random-access memory (SRAM) types by attesting/identifying the origin of the manufacturer. The proposed technique generates a single signature for a manufacturer and does not require any exhaustive registration/authentication process. We validate our proposed technique using 345 SRAM chips produced by major manufacturers. The silicon results show that the test scores ($F_{1}$ score) of our proposed technique of identifying memory manufacturer and part-number are 93% and 71%, respectively.Comment: This manuscript has been submitted for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Diagnostic Radiology in Liberia: A Country Report

Liberia is a tropical country located south of the Sahara Desert in coastal West Africa. It lies at 6 °30’ North Latitude and 9° 30’ West Longitude and is bordered by Guinea, Cote d’Ivoire, Sierra Leone and the Atlantic Ocean. Liberia has three distinct topographical areas: 1) coastal plain, creeks, lagoons and mangrove swamps; 2) rolling, forested hills with elevations up to 500 feet that cover most of the country; and 3) low mountains and plateaus in the Northern highlands with elevations reaching 4,748 feet (Nimba Mountains). Liberia is home to approximately four million people and is roughly the size of the US state of Tennessee. Named after former US President James Monroe, Liberia’s capital Monrovia is a coastal city with a population of one million (1). There are two major seasons in Liberia: dry and rainy. The dry season occurs between December and March, and is is characterized by warm days and cool nights, with risk of sand storms from the Sahara Desert (2). The rainy season occurs between mid-April and mid-November. The average annual rainfall is 200 inches on the coast and decreases to 80 inches in areas farthest inland, and the average temperature is 27 degrees Celsius (81 degrees Fahrenheit) (1). Liberia is a low-income country that relies heavily on foreign aid (3). Liberia is the seventh poorest nation in the world, ranking 31st among 46 sub-Sarahan African countries in national income. In 2013, Liberia’s per capita GDP was $900 US (3). Liberia’s economy depends heavily on natural resources, with mining and agriculture being the dominant industries. Iron exportation has grown and in 2013 overcame rubber as Liberia’s top export. According to the 2013 Central Bank of Liberia (CBL) Annual Report, iron ore and rubber represent 82% of Liberia’s total exports (4). Civil war destroyed much of Liberia’s economy, including critical infrastructure in and around Monrovia. Although conditions are favorable for agriculture, Liberia does not produce nearly enough food to meet the demands of its population. The country imports large quantities of food, with rice alone accounting for 10% of its overall imports (5)

Environmental Risks to Public Health in the United Arab Emirates: A Quantitative Assessment and Strategic Plan

Background: Environmental risks to health in the United Arab Emirates (UAE) have shifted rapidly from infectious to noninfectious diseases as the nation has developed at an unprecedented rate. In response to public concerns over newly emerging environmental risks, the Environment Agency–Abu Dhabi commissioned a multidisciplinary environmental health strategic planning project